I'll add a personal anecdote - 2 years ago, I wrote a SwiftUI app by myself (bare you, I'm mostly an infrastructure/backend guy with some expertise in front end, where I get the general stuff, but never really made anything big out of it other than stuff on LAMPP back in 2000s) and it took me a few weeks to get it to do what I want to do, with bare minimum of features. As I was playtesting my app, I kept writing a wishlist of features for myself, and later when I put it on AppStore, people around the world would email me asking for some other features. But life, work and etc. would get into way, and I would have no time to actually do them, as some of the features would take me days/weeks.
Fast forward to 2 weeks ago, at this point I'm very familiar with Claude Code, how to steer multiple agents at a time, quick review its outputs, stitch things together in my head, and ask for right things. I've completed almost all of the features, rewrote the app, and it's already been submitted to AppStore. The code isn't perfect, but it's also not that bad. Honestly, it's probably better from what I would've written myself. It's an app that can be memory intensive in some parts, and it's been doing well from my testings. On top of it, since I've been steering 2-3 agents actively myself, I have the entire codebase in my mind. I also have overwhelming amount of more notes what I would do better and etc.
My point is, if you have enough expertise and experience, you'll be able to "stitch things together" cleaner than others with no expertise. This also means, user acquisition, marketing and data will be more valuable than the product itself, since it'll be easier to develop competing products. Finding users for your product will be the hard part. Which kinda sucks, if I'll be honest, but it is what it is.
I don’t see how we get there, though, at least in the short term. We’re still living in the heavily-corporate-subsidized AI world with usage-based pricing shenanigans abound. Even if frontier models providers find a path to profitability (which is a big “if”), there’s no way the price is gonna go anywhere but up. It’s moviepass on steroids.
Consumer hardware capable of running open models that compete with frontier models is still a long ways away.
Plus, and maybe it’s just my personal cynicism showing, but when did tech ever reduce pricing while maintaining quality on a provided service in the long run? In an industry laser focused on profit, I just don’t see how something so many believe to be a revolutionary force in the market will be given away for less than it is today.
Billions are being invested with the expectation that it will fetch much more revenue than it’s generating today.
There's little evidence this is true. Even OpenAI who is spending more than anyone is only losing money because of the free version of ChatGPT. Anthropic says they will be profitable next year.
> Plus, and maybe it’s just my personal cynicism showing, but when did tech ever reduce pricing while maintaining quality on a provided service in the long run? In an industry laser focused on profit, I just don’t see how something so many believe to be a revolutionary force in the market will be given away for less than it is today.
Really?
I mean I guess I'm showing my age but the idea I can get a VM for a couple of dollars a month and expect it to be reliable make me love the world I live in. But I guess when I started working there was no cloud and to get root on a server meant investing thousands of dollars.
According to Ed Zitron, Anthropic spent more than it's total revenue in the first 9 months of 2025 on AWS alone: $2.66 billion on AWS compute on an estimated $2.55 billion in revenue. That's just AWS, not payroll, not other software or hardware spend. He's regularly reporting concrete numbers that look horrible for the industry while hyperscalers and foundation model companies continue to make general statements while refusing to get specific or release real revenue figures. If you only listen to what the CEOs are saying, then sure it sounds great.
Anthropic also said that AI would be writing 95% of code in 3 months or something, however many months ago that was.
Yes, but it's unclear how much of that is training costs vs operational costs. They are very different things.